Research On Maximum Power Point Tracking Methods Of Photovoltaic Power Generation System

Solar energy is clean,pollution-free,widely distributed,and inexhaustible.It will surely become the main energy source of humanity in the future.At present,the main form of utilization of solar energy is photovoltaic power generation.As the basis of the photovoltaic power generation system,photovoltaic cells are expensive and the output characteristics are greatly affected by the environment.In order to minimize energy loss and save costs,it is essential to increase utilization.In the current method of improving the utilization rate,using maximum power point tracking(Maximum Power Point Tracking,MPPT)algorithm is the most economical method.To maximize the use of energy,MPPT has become an indispensable part of the photovoltaic power generation system.However,the current photovoltaic MPPT algorithm has the problem of slow tracking speed or poor accuracy.Therefore,this article aims to study the photovoltaic MPPT algorithm and proposes improved MPPT algorithms in the case of single peak and multi-peak.The main work of this article is as follows.Firstly,the research background and significance of photovoltaic power generation are introduced,and the development status of photovoltaic power generation industry and MPPT algorithm at home and abroad is expounded.Analyzed the working principle of photovoltaic cells,established mathematical models of photovoltaic cells and photovoltaic arrays,and analyzed the influence of temperature and light intensity changes on their output characteristics,which laid the foundation for the MPPT algorithm innovation below.Secondly,aiming at the problems of slow tracking speed and poor accuracy of the traditional incremental conductance method,an improved single-peak MPPT control algorithm based on the incremental conductance method is proposed.This method improves the step size of the traditional incremental conductance method,uses constant voltage startup to reduce the tracking time,and introduces a particle swarm optimization algorithm to reduce the oscillation at steady state.Then the light intensity and temperature were changed respectively and the simulation comparisonbetween the proposed method and the traditional method was carried out.The result proves that the proposed method has improved tracking speed,tracking accuracy and dynamic response ability compared with the traditional conductance incremental method.Finally,for the problem that the basic particle swarm algorithm is prone to slow tracking speed and more oscillation during the multi-peak maximum power point tracking,an improved multi-peak MPPT control method based on particle swarm algorithm is proposed.The algorithm first determines the maximum power point range according to the 0.8 times voltage method,then improves the learning factor and inertia weight coefficient of the basic particle swarm optimization algorithm,and uses the improved algorithm to accurately track the maximum power point.The simulation results show that the improved multi-peak algorithm can track the maximum power point more quickly and accurately than the basic particle swarm algorithm under the conditions of uniform illumination,constant shadow and dynamic shadow.